Staff Data Scientist - Supply Chain in London

Staff Data Scientist - Supply Chain in London

London Full-Time 70000 - 90000 £ / year (est.) No working from home possible
O

At a Glance

  • Tasks: Lead data science projects to optimise supply chain and enhance forecasting models.
  • Company: Join a dynamic team at On, revolutionising supply chain with AI/ML.
  • Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on innovation and career development.
  • Why this job: Make a real impact on global supply chain efficiency and decision-making.
  • Qualifications: 8+ years in data science, expertise in Python, SQL, and optimisation software.

The predicted salary is between 70000 - 90000 £ per year.

As a Staff Data Scientist in Supply Chain, you will play a pivotal role in shaping the future of On’s supply chain. You are a technical leader within our data science team, responsible for designing, developing, and deploying cutting‑edge optimization solutions and advanced forecasting models. Your work will have a topline impact on our ability to optimize inventory, improve planning accuracy, and make data‑driven decisions at a global scale. You will tackle our most complex and ambiguous challenges in our supply chain.

Your Mission:

  • Position data science to drive topline impact on the supply chain, reducing stockouts and ensuring orders are met in full, through evaluating the space and providing clarity on what needs to happen from both a technology, algorithm, and process perspective to achieve results.
  • Design, develop, and implement state‑of‑the‑art optimization models to drive a more efficient, resilient, and reliable supply chain.
  • Lead complex, end‑to‑end optimization projects from conception to deployment, ensuring they meet business needs and are scalable and robust.
  • Provide guidance on forecasting approaches and how they impact supply chain optimisation and performance.
  • Collaborate with senior stakeholders across the organization, including Demand Planning, Supply Planning, Product, and Controlling, to guide supply chain strategy so that it can best take advantage of data & AI.
  • Act as a thought leader in the field of supply chain optimisation and forecasting, staying abreast of the latest research and technologies and identifying opportunities to apply them at On.
  • Mentor and coach other data scientists, providing technical guidance and helping them grow in their careers.
  • Contribute to the development of our data science platform and infrastructure, ensuring we have the tools and processes to build and deploy models efficiently.

Qualifications:

  • A deep understanding of statistical modeling, machine learning, and time‑series forecasting.
  • 8+ years of experience in data science, with a focus on optimisation in the context of supply chains.
  • Experience building forecasting models is also desired.
  • A Master’s or Ph.D. in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline.
  • A hands‑on‑keyboard data scientist who is also a strategic thinker.
  • Expertise in Python and SQL, and experience with data science libraries such as Pandas, NumPy, Scikit‑learn, and TensorFlow/PyTorch.
  • Experience deploying and maintaining machine learning and optimisation models in a production environment.
  • Experience with optimisation software such as (but not limited to) Gurobi, as well as fluency in large‑scale data processing and distributed computing frameworks (e.g. Spark).
  • A strong communicator who can build relationships with stakeholders at all levels of the organization.
  • Passionate about using data to drive business impact and excited about the opportunity to shape the future of On’s supply chain.

About the Team:

You will be part of a growing and diverse team of ML engineers, data scientists, data engineers, and product managers passionate about revolutionising how we leverage AI/ML to solve complex challenges across On. We focus on building and operating the creative and impactful models that personalise experiences, optimise decision‑making, and predict future trends. The team operates in a fast‑paced environment and is used to rapid turnaround times and ambitious targets. The shared goal is efficient growth at high speed, ensuring our ML systems scale with On's needs.

On is an Equal Opportunity Employer. We are committed to creating a work environment that is fair and inclusive, where all decisions related to recruitment, advancement, and retention are free of discrimination.

Staff Data Scientist - Supply Chain in London employer: ON.com

At On, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Staff Data Scientist in Supply Chain, you will not only have the opportunity to lead cutting-edge projects but also benefit from a supportive environment that prioritises employee growth through mentorship and continuous learning. Our commitment to diversity and inclusion ensures that every team member's voice is valued, making On a truly rewarding place to advance your career while making a significant impact on our global supply chain.

O

Contact Details:

ON.com Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff Data Scientist - Supply Chain in London

Tip Number 1

Network like a pro! Reach out to current employees at On or in the supply chain optimisation field. A friendly chat can give you insider info and might just land you a referral.

Tip Number 2

Show off your skills! Prepare a portfolio showcasing your best optimisation models and forecasting projects. When you get that interview, you’ll have tangible examples to impress the hiring team.

Tip Number 3

Stay updated on industry trends! Read up on the latest research in data science and supply chain optimisation. Being able to discuss current technologies will show you’re passionate and knowledgeable.

Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the On team.

We think you need these skills to ace Staff Data Scientist - Supply Chain in London

Statistical Modelling
Machine Learning
Time-Series Forecasting
Optimisation
Python
SQL
Data Science Libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch)

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the Staff Data Scientist role. Highlight your experience in supply chain optimisation and any relevant projects you've led. We want to see how your skills align with our mission!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for data science and how you can drive impact at On. Don’t forget to mention specific examples of your work that relate to the job description.

Showcase Your Technical Skills:We’re looking for a hands-on data scientist, so be sure to highlight your expertise in Python, SQL, and any optimisation software you’ve used. Mentioning your experience with machine learning libraries will definitely catch our eye!

Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensure it gets the attention it deserves!

How to prepare for a job interview at ON.com

Know Your Models Inside Out

Make sure you can discuss your experience with statistical modelling, machine learning, and time-series forecasting in detail. Be prepared to explain how you've applied these techniques in supply chain optimisation and the impact they had on business outcomes.

Showcase Your Leadership Skills

As a Staff Data Scientist, you'll be expected to mentor others and lead projects. Think of examples where you've guided teams or made strategic decisions. Highlight your ability to communicate complex concepts clearly to stakeholders at all levels.

Familiarise Yourself with Tools and Technologies

Brush up on your knowledge of Python, SQL, and relevant data science libraries like Pandas and TensorFlow. Be ready to discuss your experience with optimisation software such as Gurobi and large-scale data processing frameworks like Spark.

Prepare for Scenario-Based Questions

Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've faced in previous roles and how you approached them, especially in terms of optimising supply chains and improving planning accuracy.